Synthesis of the Supremal Covert Attacker Against Unknown Supervisors by Using Observations
Ruochen Tai, Liyong Lin, Yuting Zhu, Rong Su

TL;DR
This paper presents a method for synthesizing the most powerful covert attacker against unknown supervisors in a control system, using limited observational data to ensure damage reachability and covertness, with proven decidability.
Contribution
It introduces a novel approach to synthesize supremal covert attackers without knowing the supervisor model, using observations and transforming the problem into safe supervisor synthesis.
Findings
Decidability of the observation-assisted covert attacker synthesis problem.
Effective synthesis demonstrated on a water tank example.
Addresses the gap between known and unknown supervisor models.
Abstract
In this paper, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synthesized attacker needs to ensure both the damage-reachability and the covertness against all the supervisors which are consistent with the given set of observations. There is a gap between the de facto supremality, assuming the model of the supervisor is known, and the supremality that can be attained with a limited knowledge of the model of the supervisor, from the adversary's point of view. We consider the setup where the attacker can exercise sensor replacement/deletion attacks and actuator enablement/disablement attacks. The solution methodology proposed in this work is to reduce the…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Adversarial Robustness in Machine Learning
